The rising complexity of cyber threats demands tailored cybersecurity training, especially for critical infrastructure sectors such as healthcare, energy, telecommunications, and maritime. This paper examines the training needs of professionals in these domains, emphasizing the importance of customized Training Programmes that address sector-specific challenges and workforce diversity. For this study, two tailored questionnaires were developed to address the distinct needs and perspectives of IT and non-IT personnel. This distinction was crucial to capture the diverse challenges and priorities faced by these groups, ensuring a more holistic understanding of organizational training requirements. By incorporating these diverse perspectives, the study aims to bridge critical gaps in training and awareness, enabling organizations to design more inclusive and impactful cybersecurity programs. The findings guide the development of effective Cyber Range training initiatives, providing actionable recommendations to enhance cybersecurity preparedness in critical infrastructures. These include strategies for building competences that contribute to the protection of sector-related supply chains, promoting the reusability of Cyber Range training scenarios to improve resource efficiency, and tailoring scenarios to sector-specific challenges for greater relevance. All efforts should focus on building a cyber resilient ecosystem for critical infrastructures to address the current and future cyber threat landscape. The study was performed in the context of SecAwarenessTruss project, that emphasizes the role of Cyber Ranges in delivering hands-on, realistic training to enhance organizational resilience.

This paper covers the problem of interference generated by sensor nodes in Wireless Sensor Networks (WSNs). The interference affects the link quality of wireless communications, thus the Quality of Service (QoS) of Internet of Things (IoT) applications. The interference is the effect of the transmission of a cluster of nodes, at a certain power which is not always efficiently set, or calibrated. In addition, using unnecessary high power values impacts the waste of the node energy. Therefore, we address the interference problem by means of Transmission Power Control (TPC), for spatial reuse across the networks, which allows simultaneous point-to-point communications. Given the dynamics and unpredictability of the wireless channel, theoretical and empirical solutions are too slow, inefficient and memoryless for the problem we are facing. Our proposed protocol, QL-TPC, integrates reinforcement learning with game theory, within the IEEE 802.15.4 standard, at the MAC layer, to learn the combination of power levels per node, through indirect cooperation. The goal is to define the minimum transmission power, related to the density of the network, while respecting the QoS requirements and saving energy. QL-TPC is implemented in Atmel Zigbit, real world sensor devices, and is tested in a Faraday cage. We show the results, focusing on the aspect of reliability, energy efficiency, convergence and scalability. The nodes that use our protocol are estimated to have longer lifetime in order of months, while keeping same performance, than the homogeneous case.

Video content providers put stringent requirements on the quality assessment methods realized on their services. They need to be accurate, real-time, adaptable to new content, and scalable as the video set grows. In this letter, we introduce a novel automated and computationally efficient video assessment method. It enables accurate real-time (online) analysis of delivered quality in an adaptable and scalable manner. Offline deep unsupervised learning processes are employed at the server side and inexpensive no-reference measurements at the client side. This provides both real-time assessment and performance comparable to the full reference counterpart, while maintaining its no-reference characteristics. We tested our approach on the LIMP Video Quality Database (an extensive packet loss impaired video set) obtaining a correlation between 78% and 91% to the FR benchmark (the video quality metric). Due to its unsupervised learning essence, our method is flexible and dynamically adaptable to new content and scalable with the number of videos.

The objective of this work is to investigate potential accuracy improvements in the fingerprint-based indoor positioning processes, by imposing map-constraints into the positioning algorithms in the form of a-priori knowledge. In our approach, we propose the introduction of a Route Probability Factor (RPF), which reflects the possibility of a user, to be located on one position instead of all others. The RPF does not only affect the probabilities of the points along the pre-defined frequent routes, but also influences all the neighbouring points that lie at the proximity of each frequent route. The outcome of the evaluation process, indicates the validity of the RPF approach, demonstrated by the significant reduction of the positioning error.

This work proposes the use of 3D Ray Tracing (RT) to construct radiomaps for WLAN Received Signal Strength (RSS) fingerprint-based positioning, in conjunction with calibration techniques to tackle with the problem using different devices. In addition to the fact that RSS data collection might be a tedious and time-consuming process, the measured radiomap accuracy and applicability is subject to potential changes in the wireless environment. Therefore, RT becomes a very suitable and efficient solution to tackle this problem. Moreover, in traditional fingerprint-based methods, the underlying radiomap is restricted to the mobile device for which the radiomap has been created. To overcome this limitation, we propose the use of linear data transformation to match the characteristics of various devices. We address both challenges by using 3D RT-generated radiomaps and highlight the efficiency of this approach in terms of the time spent to create the radiomap, the amount of data required to calibrate the radiomap for different devices and the positioning error which is compared against the case of using dedicated radiomaps collected with each device.

A novel, multi-slope dual breakpoint model for predicting path-loss in ultra-wideband (UWB) off-body communication channels, is proposed. This model is based on real-body measurements, carried out in the frequency range between 3.5GHz-6.5GHz, in an anechoic chamber. New parameters that describe this specific propagation environment are presented and evaluated. Results show that the first breakpoint point angle lies in the lit region of the transmitter and increases exponentially with distance until it rises to its threshold value. Based on this finding the near and far field areas for BAP (body to access point) channels are defined. In addition, newly estimated decay coefficients suggest severe degradation as the receiver moves in between the two critical angles. Finally, techniques for model expansion in two dimensions are discussed.

This paper presents wideband characteristics of a low elevation, land mobile, single satellite, dual circularly polarized, multiple-input multiple-output (MIMO) radio propagation channel. The work is based on S-band measurements using an artificial platform to represent the satellite, situated on a hilltop, to a mobile vehicle located in three environments: tree-lined road, suburban and urban. First and second order statistics and inter-tap cross-correlations are derived for both large and small scale fading, over the delay and combined spatial/polarization domains from the measured 2times2 MIMO matrix channel data. The work is aimed towards further development of a valid wideband land mobile satellite (LMS) MIMO channel model. Such systems may form the next generation of satellite delivered mobile broadband Internet services.

This paper presents inclusive details of a measurement campaign carried out in Guildford, UK, during the summer of 2005, where the land dual-antenna mobile, dual-satellite MIMO channel at S band frequencies was characterized. Two emulated, adjacently positioned, low elevation satellites, each with a right hand circular polarized antenna, communicate with a vehicle containing two co-polarized antennas. This measurement setup is aimed at being representative of a geostationary MIMO satellite cluster scenario. Narrowband measured characteristics of the land mobile satellite-MIMO channel are presented, and show the harsh channel to be overcome, with 1% of channels reaching more than 40 dB beyond free space loss. The experimental channel data obtained for this 2times2 MIMO system is investigated for possible capacity improvement, over a single satellite SISO system. It is shown that a near doubling in median and 10% outage capacity is achievable from a 2times2 land mobile satellite MIMO system compared with a SISO system, highlighting some advantages of satellite MIMO systems.

Movement of vegetation structures introduces an adverse environment for high frequency radiowave propagation. This paper examines a series of vegetation scattering measurement campaigns during various wind conditions. The measurements were divided into controlled and outdoor environments. The controlled environment measurements were conducted in an anechoic chamber at 0.9, 2, 12 and 17GHz. The outdoor measurements were carried out at 1.8GHz and involved in recording of a transmitted signal originating from an existing Digital Cellular System (DCS-1800) base station. The obtained results are discussed and presented in terms of their first- and second-order statistics. Analysis demonstrates that the received signal behaviour is highly wind dependent, especially when the environment is changing from calm to a windy condition. The signal fast-fading is found to be Rician distributed and an empirical model of the k-factor variation over wind speed is also presented.

A modelling approach is presented, based on a modified form of the Fresnel diffraction integral. The approach combines contributions through different building elements and interfaces, e.g., windows, walls and doors, in order to-calculate the overall signal contributed to a certain point inside a building. The method could be used to investigate coverage and interference issues when overlaying line of site microcells with in-building picocells or similar scenarios where there is a line of site with the building of interest. Two different cases are considered depending on the receiver position within the building. The first case refers to a receiver position in the first room next to the external wall, while the second case refers to a position anywhere else in the building. The predicted results are compared with a set of measured data recorded in 3 different UK cities.